Neural Network Models for Abduction Problems Solving

  • Viorel Ariton
  • Doinita Ariton
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4692)


Due to its’ connectionist nature, abductive reasoning may get neural network implementations that yet require structure adaptation to the abduction problems which Bylander and the team asserted. The paper proposes neural models for all known abduction problems, in a really unified manner, and with a sound and straightforward embedding in the existing neural network paradigms.


Neural Network Model Fault Diagnosis Input Function Neural Model Truth Table 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Ariton, V., Ariton, D.: A General Approach for Diagnostic Problems Solving by Abduction. In: Proc. of IFAC-SAFEPROCESS, Budapest, Hungary, pp. 446–451 (2000)Google Scholar
  2. 2.
    Ayeb, B., Wang, S., Ge, J.: A Unified Model for Abduction-Based Reasoning. IEEE Trans. on Systems Man and Cybernetics - Part A: Systems and Humans 28(4), 408–424 (1998)CrossRefGoogle Scholar
  3. 3.
    Bylander, T., Allemang, D., Tanner, M.C., Josephson, J.R.: The Computational Complexity of Abduction. Artificial Intelligence 49, 25–60 (1991)zbMATHCrossRefGoogle Scholar
  4. 4.
    Goel, A., Ramanujam, J.: A Neural Architecture for a Class of Abduction Problems. IEEE Transactions on Systems Man and Cybernetics 26(6), 854–860 (1996)CrossRefGoogle Scholar
  5. 5.
    Peng, Y., Reggia, J.: Abductive Inference Models for Diagnostic Problem Solving. Springer, Heidelberg (1990)zbMATHGoogle Scholar
  6. 6.
    Wang, S., Ayeb, B.: Diagnosis: Hypothetical Reasoning With A Competition-Based Neural Architecture. In: Proc. International Joint Conference on Neural Networks, vol. I, pp. 7–12 (1992)Google Scholar
  7. 7.
    Xu, Y., Zhang, C.: An improved Critical Diagnosis Reasoning Method. In: ICTAI, Toulouse, France, vol. 1, pp. 170–173 (1996)Google Scholar
  8. 8.
    Zell, A., Mache, N., Sommer, T., Korb, T.: SNNS- Neural Network Simulator, User Manual. University of Tuebingen (1991)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Viorel Ariton
    • 1
  • Doinita Ariton
    • 2
  1. 1.“Danubius” University, Lunca Siretului no. 3, 800416, GalatiRomania
  2. 2.“Dunarea de Jos” University, Domneasca no. 47, 800001, GalatiRomania

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